Abstract

Nowadays, mobile multitasking takes quite some steps, especially while looking for a less frequently used application, which brings the need of optimizing mobile multitasking to make it smoother and faster.
In this thesis, I looked into the collaboration of interface design and prediction algorithm, aiming at providing a better mobile multitasking solution which is easy to control and fast to use. My work mainly includes two aspects: new gesture control method for reducing the operation steps while switching between multiple applications; new application recommendation algorithm to reduce the time and effort of reaching target applications.
I applied my findings to a mobile application launcher, SwipeLauncher, which defined a new gesture control method with fast access to certain applications. To validate my design, I first used model-based method for making design decisions, including the menu layout design and number of applications in the launcher.
Afterwards, I conducted an experiment with SwipeLauncher and Android home screen’s performance for opening designated applications. The evaluation indicators include operation speed, accuracy, system complexity and user comfort. SwipeLauncher gets better performance in most dimensions: using SwipeLauncher is 34.2% faster than Android home screen, with lower error rate and ignore rate. SwipeLauncher can be used as an alternative of Android home screen in the future for mobile multitasking optimization.